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Non - invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps.
- Source :
-
Computer Methods in Biomechanics & Biomedical Engineering . Sep2020, Vol. 23 Issue 12, p879-887. 9p. - Publication Year :
- 2020
-
Abstract
- Cardiovascular diseases (CVD) and strokes produce immense health and economic burdens globally. Coronary Artery Disease (CAD) is the most common type of cardiovascular disease. Coronary Angiography, which is an invasive approach for detection and treatment, is also the standard procedure for diagnosing CAD. In this work, we illustrate a Medical Decision Support System for the prediction of Coronary Artery Disease (CAD) using Fuzzy Cognitive Maps (FCM). FCMs are a promising modeling methodology, based on human knowledge, capable of dealing with ambiguity and uncertainty and learning how to adapt to the unknown or changing environment. The newly proposed MDSS is developed using the basic notions of Fuzzy Cognitive Maps and is intended to diagnose CAD utilizing specific inputs related to the patient's clinical conditions. We show that the proposed model, when tested on a dataset collected from the Laboratory of Nuclear Medicine of the University Hospital of Patras achieves accuracy of 78.2% outmatching several state-of-the-art classification algorithms. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10255842
- Volume :
- 23
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Computer Methods in Biomechanics & Biomedical Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 146599749
- Full Text :
- https://doi.org/10.1080/10255842.2020.1768534